Analysis and Visualization of Network Data using JUNG

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Network position: a key component in the characterization of social personality types (2012, methodology): “We used the programming language Java and the Java Universal Network/Graph Framework JUNG version 2.0.1 (Madadhain et al. 2005).”
Towards comprehensive support for organizational mining (2008, methodology): “We use the JUNG (Java Universal Network/Graph) library [39] to implement the plug-in.”
Analyzing (social media) networks with NodeXL (2009, methodology): “Researchers have created toolkits from sets of network analysis components not limited to R and the SNA library, JUNG, Guess, and Prefuse [[2], [12], [15]].”
Graph-of-word and TW-IDF: new approach to ad hoc IR (2013, methodology): “The graph visualization has been automatically generated using the Kamada-Kawai force-based algorithm [11] and the JUNG library [19].”
ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems (2010, methodology): “Network images are generated using the JAVA JUNG (20) libraries for analysis and visualization of network data.”
SNAP: A General Purpose Network Analysis and Graph Mining Library (2016, background): “Similarly, there are several userfriendly libraries that implement dozens of network analysis algorithms [Batagelj and Mrvar 1998; Csardi and Nepusz 2006; Gregor and Lumsdaine 2005; Hagberg et al. 2008; O’Madadhain et al. 2005].”